RESEARCH: CANCER
FOLDING PROJECT #14932 PROFILE

PROJECT TEAM

Manager(s): Prateek Bansal
Institution: University of Illinois Urbana-Champaign

WORK UNIT INFO

Atoms: 105,129
Core: OPENMM_22
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project looks at Class F Receptors, which help control how cells develop. When these receptors are overactive, it can lead to cancers like Basal Cell Carcinoma and Medulloblastoma. By using computer simulations, researchers hope to learn how these receptors work so they can better understand and treat these diseases.

Note: This TLDR is a simplication and may not be 100% accurate.

OFFICAL PROJECT DESCRIPTION

Class F Receptors Class F Receptors are involved in the control of cell differentiation.

Over-activation of these proteins have links to Basal Cell Carcinoma and Medulloblastoma.

Through Simulations we aim to understand the activation mechanisms of these proteins, giving us a way to probe into the pathogenesis of the disease.

RELATED TERMS GLOSSARY AI BETA

Note: Glossary items are a high level summary and may not be 100% accurate.

Class F Receptors

A family of G protein-coupled receptors involved in cell differentiation.

Scientific: Biotechnology
Cellular Biology / Signaling Pathways

Class F Receptors are a type of protein found on the surface of cells. They play a crucial role in regulating how cells develop and specialize. When these receptors are overactive, it can lead to the development of certain cancers, such as Basal Cell Carcinoma and Medulloblastoma. By studying how these receptors work, researchers hope to find new ways to treat these diseases.


Basal Cell Carcinoma

A type of skin cancer that originates in the basal cells.

Pathological: Healthcare
Oncology / Skin Cancer

Basal Cell Carcinoma is a common type of skin cancer that starts in the basal cells, which are found in the deepest layer of the epidermis. It typically appears as a pearly or waxy bump and can grow slowly over time. Treatment options include surgery, radiation therapy, and topical medications.


Medulloblastoma

A type of aggressive brain cancer that develops in the cerebellum.

Pathological: Healthcare
Oncology / Brain Cancer

Medulloblastoma is a malignant tumor that originates in the cerebellum, the part of the brain responsible for balance and coordination. It is most common in children and can spread to other parts of the body. Treatment typically involves surgery, radiation therapy, and chemotherapy.


Simulations

The use of computer models to mimic real-world processes.

Scientific Method: Biotechnology
Computational Biology / Molecular Modeling

Simulations are a powerful tool used in science and engineering to understand complex systems. By creating computer models that represent real-world phenomena, researchers can test hypotheses, explore different scenarios, and gain insights that would be difficult or impossible to obtain through traditional experiments.


Pathogenesis

The development and progression of a disease.

Scientific: Pharmaceutical
Medical Research / Disease Mechanisms

Pathogenesis refers to the biological processes that lead to the onset and development of a disease. Understanding the pathogenesis of a particular disease is essential for developing effective treatments.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Tuesday, 14 April 2026 06:32:42
Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average
1 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 7,588,742 143,996 52.70 0 hrs 27 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 6,928,571 137,765 50.29 0 hrs 29 mins
3 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 6,164,143 131,381 46.92 0 hrs 31 mins
4 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 5,831,365 133,814 43.58 0 hrs 33 mins
5 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 5,086,506 126,889 40.09 0 hrs 36 mins
6 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 4,624,895 122,468 37.76 0 hrs 38 mins
7 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 4,580,401 122,734 37.32 0 hrs 39 mins
8 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 4,512,553 122,677 36.78 0 hrs 39 mins
9 RTX A5000
GA102GL [RTX A5000]
Nvidia GA102GL 4,491,302 122,079 36.79 0 hrs 39 mins
10 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 4,177,421 120,030 34.80 0 hrs 41 mins
11 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,961,178 116,864 33.90 0 hrs 42 mins
12 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 3,207,614 108,763 29.49 0 hrs 49 mins
13 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,955,053 103,742 28.48 0 hrs 51 mins
14 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 2,630,269 102,659 25.62 0 hrs 56 mins
15 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,310,848 98,300 23.51 1 hrs 1 mins
16 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,205,788 94,833 23.26 1 hrs 2 mins
17 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 2,133,136 95,136 22.42 1 hrs 4 mins
18 GeForce RTX 2060 12GB
TU106 [GeForce RTX 2060 12GB]
Nvidia TU106 2,091,295 93,007 22.49 1 hrs 4 mins
19 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 2,085,360 95,319 21.88 1 hrs 6 mins
20 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 2,021,064 93,809 21.54 1 hrs 7 mins
21 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,448,406 84,648 17.11 1 hrs 24 mins
22 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,367,249 82,389 16.60 1 hrs 27 mins
23 GeForce RTX 2060 Mobile / Max-Q
TU106M [GeForce RTX 2060 Mobile / Max-Q]
Nvidia TU106M 1,308,036 81,730 16.00 1 hrs 30 mins
24 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,148,637 77,573 14.81 1 hrs 37 mins
25 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,108,121 77,003 14.39 1 hrs 40 mins
26 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,046,244 74,201 14.10 1 hrs 42 mins
27 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,009,930 74,243 13.60 1 hrs 46 mins
28 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 721,323 65,660 10.99 2 hrs 11 mins
29 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 586,048 62,846 9.33 2 hrs 34 mins
30 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 573,187 61,821 9.27 2 hrs 35 mins
31 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 561,219 60,958 9.21 2 hrs 36 mins
32 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 470,080 57,759 8.14 2 hrs 57 mins
33 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 418,153 54,022 7.74 3 hrs 6 mins
34 GeForce GTX 980M
GM204 [GeForce GTX 980M] 3189
Nvidia GM204 325,028 51,443 6.32 3 hrs 48 mins
35 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 309,196 50,376 6.14 3 hrs 55 mins
36 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 301,637 50,062 6.03 3 hrs 59 mins
37 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 226,949 45,249 5.02 4 hrs 47 mins
38 GeForce GTX 770
GK104 [GeForce GTX 770] 3213
Nvidia GK104 146,194 39,158 3.73 6 hrs 26 mins
39 GeForce GTX 680
GK104 [GeForce GTX 680] 3250
Nvidia GK104 125,340 37,364 3.35 7 hrs 9 mins
40 GeForce GTX 660 Ti
GK104 [GeForce GTX 660 Ti] 2634
Nvidia GK104 98,619 34,528 2.86 8 hrs 24 mins
41 GeForce GTX 660
GK106 [GeForce GTX 660]
Nvidia GK106 68,000 30,496 2.23 10 hrs 46 mins
42 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 50,936 27,725 1.84 13 hrs 4 mins
43 GTX 650 Ti Boost
GK106 [GTX 650 Ti Boost]
Nvidia GK106 43,041 22,243 1.94 12 hrs 24 mins
44 GeForce GT 730
GK208B [GeForce GT 730] 692.7
Nvidia GK208B 15,400 16,800 0.92 26 hrs 11 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Tuesday, 14 April 2026 06:32:42
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make